Table 2 Accuracy score comparison across different classification ML algorithms.
Classification ML Algorithms | Feature Extraction Methods | |
|---|---|---|
| Â | TF-IDF | Bag of n-grams |
Logistic Regression | 97.92% | 98.71% |
Decision Tree Classifier | 93.56% | 94.25% |
Gradient Boosting Classifier | 95.75% | 96.05% |
Random Forest Classifier | 98.23% | 91.77% |
Support Vector Classifier | 99.90% | 99.43% |
XGBoost Classifier | 99.98% | 99.98% |
